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Figure 8. Top: Sector scan sonar showing the narrow receive beams for detection and even narrower ones for classification. Bottom: so- nar image for ping 61 as the fast surface watercraft continues its U- turn. From Ferguson and Lo (2011).
processor estimated the instantaneous polar position of the craft (i.e., the end point of the wake) to be 181.4 m and 5.9°, the speed of the craft to be 4.6 m/s, and the heading to be −167.7°. Any offset of the wake from the track is caused by the wake drifting with the current.
The sonar is the primary sensor and, under the rules of en- gagement, a rapid layered response is now possible using a combination of nonlethal, less than lethal, and (last resort) lethal countermeasures.
Conclusion
The application of the principles and practice of acoustic sys- tems science and engineering has improved the detection, classification, localization, and tracking processes for the Submarine Force, Land Force, and Mine Countermeasures Force, leading to enhanced situational awareness. Acoustic systems will continue to play a crucial role in operational sys- tems, with new sensing technologies and signal-processing and data fusion methods being developed for the next gen- eration of defense forces and homeland security.
Acknowledgments
I am grateful to the following Fellows of the Acoustical So- ciety of America, who taught and inspired me over three decades: Ed Sullivan, Jim Candy, and Cliff Carter in sonar signal processing; Howard Schloemer in submarine sonar array design; Bill Carey, Doug Cato, and Gerald D’Spain in underwater acoustics; Tom Howarth and Kim Benjamin in ultrawideband sonar transducers; R. Lee Culver and Whit- low Au in high-frequency sonar; and Mike Scanlon in battle- field acoustics. In Australia, much was achieved through col- laborative work programs with Ron Wyber in the research, development, and demonstration of acoustic systems science and engineering for defense.
References
Ferguson, B. G. (1990). Sharpness applied to the adaptive beamforming of acoustic data from a towed array of unknown shape. The Journal of the Acoustical Society of America 88, 2695-2701.
Ferguson, B. G. (1993a). Remedying the effects of array shape distortion on the spatial filtering of acoustic data from a line array of hydrophones. IEEE Journal of Oceanic Engineering 18, 565-571.
Ferguson, B. G. (1993b). Improved time-delay estimates of underwater acoustic signals using beamforming and prefiltering techniques. In G. C. Carter (Ed.), Coherence and Time Delay Estimation. IEEE Press, New York, pp. 85-91.
Ferguson, B. G. (1996). Time-frequency signal analysis of hydrophone data. IEEE Journal of Oceanic Engineering 21, 537-544.
Ferguson, B. G. (1998). Minimum variance distortionless response beam- forming of acoustic array data. The Journal of the Acoustical Society of America 104, 947-954.
Ferguson, B. G. (2016). Source parameter estimation of aero-acoustic emit- ters using non-linear least squares and conventional methods. IET Journal on Radar, Sonar & Navigation 10(9), 1552-1560. https://doi.org/10.1049/ iet-rsn.2016.0147.
Ferguson, B. G., and Cleary, J. L. (2001). In situ source level and source posi- tion estimates of biological transient signals produced by snapping shrimp in an underwater environment. The Journal of the Acoustical Society of America 109, 3031-3037.
Ferguson, B. G., Criswick, L. G., and Lo, K. W. (2002). Locating far-field im- pulsive sound sources in air by triangulation. The Journal of the Acoustical Society of America 111, 104-116.
Ferguson, B. G., and Culver, R. L. (2014). International student challenge problem in acoustic signal processing. Acoustics Today 10(2), 26-29.
Ferguson, B. G., and Lo, K. W. (2011). Sonar signal processing methods for de- tection and localization of fast surface watercraft and underwater swimmers in a harbor environment. Proceedings of the International Conference on Under- water Acoustic Measurements, Kos, Greece, June 20-24, 2011, pp. 339-346.
Ferguson, B. G., Lo, K. W., and Wyber, R. J. (2007). Acoustic sensing of direct and indirect weapon fire. Proceedings of the 3rd International Con- ference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2007), Melbourne, Victoria, Australia, December 3-6, 2007, pp. 167-172.
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